Amnestic MCI is often considered an early clinical stage of AD, but its subtle presentation leads to infrequent neurological evaluations. Early plasma biomarker screening during routine check-ups in community hospitals could enhance aMCI detection rates. Advances in proteomics, particularly mass spectrometry, have enabled the detection of low-abundance plasma proteins, opening new possibilities for aMCI biomarker identification. This study included 84 participants from the STAR cohort. We utilized deep plasma proteomics to detect low-abundance proteins, enriched with biofunctional magnetic beads. An early diagnostic model for aMCI was developed through bioinformatics and machine learning, with performance compared to the Simoa assay.